def test_regionset_merge(self):
nregions = 50
sizepc = Region([0] * 2, [0.5] * 2)
first = RegionSet.from_random(nregions,
Region([0] * 2, [10] * 2),
sizepc=sizepc,
precision=1)
second = RegionSet.from_random(nregions,
Region([0] * 2, [100] * 2),
sizepc=sizepc,
precision=1)
third = RegionSet(dimension=2)
third.streamadd([
Region([-1] * 2, [10] * 2),
Region([-10, 0], [0, 100]),
Region([-100, -10], [10, 10])
])
merged = RegionSet.from_merge([first, second, third])
regionkeys = []
for region in merged:
regionkeys.append(region.id)
for regions in [first, second, third]:
self.assertTrue(merged.bounds.encloses(regions.bbox))
self.assertEqual(len(first) + len(second) + len(third), len(merged))
self.assertEqual(len(regionkeys), len(set(regionkeys)))
def test_nxgraph_sweepctor_graph(self):
dimension = self.test_regions[0].dimension
nxgraph = NxGraph(dimension=dimension)
self._naive_ctor(nxgraph)
regionset = RegionSet(dimension=dimension)
regionset.streamadd(self.test_regions)
nxgraphsweepln = self._nxgraphctor(regionset)
nxgraphmdsweepln = self._nxgraphmdctor(regionset)
G = nxgraph.G
S = nxgraphsweepln.G
M = nxgraphmdsweepln.G
self.assertEqual(nxgraph.dimension, nxgraphsweepln.dimension)
self.assertEqual(nxgraph.dimension, nxgraphmdsweepln.dimension)
for N in [S, M]:
for node, region in G.nodes(data='region'):
self.assertTrue(node in N.node)
self.assertEqual(region, N.node[node]['region'])
for (u, v, aregion) in G.edges(data='intersect'):
self.assertTrue((u, v) in N.edges)
bregion = N.edges[u, v]['intersect']
self.assertEqual(aregion, bregion)
self.assertTrue('intersect' in aregion)
self.assertTrue('intersect' in bregion)
aintersect = aregion['intersect']
bintersect = bregion['intersect']
self.assertTrue(all([r in bintersect for r in aintersect]))
def context(cls, ctx: Context) -> Context:
"""
Given a context object (a collection of Regions or a Region
intersection graph), converts it into the other object type.
Args:
ctx: The object to be converted.
Returns:
The converted object.
"""
assert isinstance(ctx, (RegionSet, NxGraph))
if isinstance(ctx, RegionSet):
return NxGraphSweepCtor.prepare(ctx)()
else:
regions = RegionSet(dimension=ctx.dimension, id=ctx.id)
regions.streamadd([region for n, region, _ in ctx.regions])
return regions
def test_nxgraph_mdsweepctor(self):
dimension = self.test_regions[0].dimension
regionset = RegionSet(dimension=dimension)
regionset.streamadd(self.test_regions)
nxgraph = self._nxgraphmdctor(regionset)
with StringIO() as output:
for json_graph in ['node_link', 'adjacency']:
options = {'json_graph': json_graph, 'compact': True}
output.truncate(0)
NxGraph.to_output(nxgraph,
self._reset_output(output),
options=options)
#json_output = output.getvalue()
#print(f'{json_graph}:')
#print(f'{json_output}')
newgraph = NxGraph.from_source(self._reset_output(output))
self._check_nxgraph(nxgraph, newgraph)
def setUp(self):
definedset = RegionSet(dimension=2)
definedset.streamadd([
Region([0, 0], [5, 5], 'A'),
Region([2, 2], [5, 10], 'B'),
Region([1, 5], [3, 7], 'C'),
Region([3, 3], [4, 7], 'D'),
Region([-5, 5], [1, 7], 'E'),
Region([-5, 5], [2, 7], 'F'),
Region([3, 4], [5, 6], 'G')
])
bounds = Region([0] * 2, [1000] * 2)
self.regions = {'definedset': definedset}
self.subsets = {
'definedset': {
'G1': ['A', 'C', 'E', 'G'],
'G2': ['B', 'D', 'F'],
'G3': ['A', 'B', 'C', 'D']
}
}
for nregions in [pow(10, n) for n in range(1, 4)]:
for sizepc in [0.01, 0.05, 0.1]:
name = f'{nregions},{sizepc:.2f}'
sizepcr = Region([0] * 2, [sizepc] * 2)
regions = RegionSet.from_random(nregions,
bounds,
sizepc=sizepcr,
precision=1)
self.regions[name] = regions
self.subsets[name] = {}
for subsetpc in [0.01, 0.05, 0.1, 0.15, 0.2]:
size = round(subsetpc * len(regions))
if 0 < size < len(regions):
subname = f'{subsetpc:.2f}'
shuffled = regions.shuffle()
self.subsets[name][subname] = [
r.id for i, r in enumerate(shuffled) if i < size
]
def setUp(self):
definedset = RegionSet(dimension=2)
definedset.streamadd([
Region([0, 0], [5, 5], 'A'),
Region([2, 2], [5, 10], 'B'),
Region([1, 5], [3, 7], 'C'),
Region([3, 3], [4, 7], 'D'),
Region([-5, 5], [1, 7], 'E'),
Region([-5, 5], [2, 7], 'F'),
Region([3, 4], [5, 6], 'G')
])
bounds = Region([0] * 2, [1000] * 2)
self.regions = {'definedset': definedset}
for nregions in [pow(10, n) for n in range(1, 4)]:
for sizepc in [0.01, 0.05, *([] if nregions > 100 else [0.1])]:
sizerng = Region([0] * 2, [sizepc] * 2)
regions = RegionSet.from_random(nregions,
bounds,
sizepc=sizerng,
precision=1)
self.regions[f'{nregions},{sizepc:.2f}'] = regions